Micronutrient deficiency is a common health risk in developing countries, affecting a sizable portion of the world's population. For example, iron deficiency anemia impairs mental development, decreases energy, and can cause death in childbirth. Micronutrient deficiency can be assessed by measuring the levels of proteins such as ferritin, retinol binding protein (RBP), C-reactive protein (CRP), and alpha-1-acid glycoprotein (AGP), depending on the type of the deficiency.
Diagnosis of micronutrient deficiency is especially needed in remote areas with limited access to power and other resources. Low-cost portable tests tend to have low resolution, impeding measurement accuracy. High quality quantitative tests require samples to be collected and sent to a facility with the appropriate instruments. A wait time of about one month is common.
Microfluidic measurement devices have gained popularity as low-cost, point-of-care, and rapid diagnostic tools (Hu et al., Biosensors and Bioelectronics 2014, 54, 585-597; Martinez et al., Angew. Chem. Int. Ed. 2007, 46, 1318-1320). Scientists are developing microfluidic measurement devices for a wide range of functions, from rapid point-of-care measurement of liver enzyme levels to routine evaluation of heavy metal contamination in reservoir water (Pollock et al., PLoS ONE 2013, 8, e75616; Wang et al. 2014, Anal Bioanal Chem 406, 2799-2807). Many microfluidic measurement devices use either chemical reactions or antigen-antibody binding to produce a color change that correlates with the target analyte concentration (Hu et al., Biosensors and Bioelectronics 2014, 54, 585-597). Unlike their lateral flow assay (LFA) predecessors, these devices are often highly multiplexed with complex geometries and multi-color readouts. Moreover, color change may depend on time, temperature and humidity (Pollock et al., PLoS ONE 2013, 8, e75616). Together, these complexities make it difficult for a user to visually interpret the color change and accurately assign concentration values.
The increasing complexity of microfluidic measurement devices necessitates the development of novel methods for data acquisition and management to maintain assay objectivity and obtain quantitative measurements. Though several methods exist to read colorimetric assays, various constraints limit their utility. Line scan readers, such as the ESEQuant Lateral Flow System (Qiagen, CA, USA), successfully collect data from LFAs. However, they are incompatible with the complex geometries often found in microfluidic measurement devices. Charge-coupled device (CCD)-based readers capture data quickly over a wide area, but are often expensive and require skilled image analysis (Gui et al., Nanoscale Res Lett 2014, 9, 1-8). Smart phone cameras and corresponding applications capture assay images and compare assay color development to an accompanying color chart (Wang et al. 2014, Anal Bioanal Chem 406, 2799-2807). While these offer a simple, cost-effective solution for point-of-care assays, results are vulnerable to changes in environmental lighting, photo angle and depth, and differences in the make/model of the phone. Similarly, cell phone-attached, enclosed LFA readers, which attach to the back of a cell phone and use internal LEDs for illumination, continue to use a cell phone's camera making them dependent on the make/model of the phone (Mudanyali et al., Lab Chip 2012, 12, 2678). Lastly, as some of these microfluidic measurement devices are based on paper, portable light reflectance readers, which collect data on signal intensity by measuring the light reflected from the surface of an assay, lack sensitivity because they are not able to sample the density of absorbers throughout the thickness of the paper (Lee et al., Lab Chip 2010, 11, 120; Li et al., ELECTROPHORESIS 2014, 35, 1152-1159; Yamaguchi et al., Bioelectronics 2005, 21, 426-432).
In view of the above, there is an unmet need in the art for novel devices and/or methods for extracting quantitative information from microfluidic measurement devices.